Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Null Results in Brief

Lack of Association of Transforming Growth Factor-β1 Polymorphisms and Haplotypes with Prostate Cancer Risk in the Prostate, Lung, Colorectal, and Ovarian Trial

Daehee Kang, Kyoung-Mu Lee, Sue Kyung Park, Sonja I. Berndt, Douglas Reding, Nilanjan Chatterjee, Robert Welch, Stephen Chanock, Wen-Yi Huang and Richard B. Hayes
Daehee Kang
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kyoung-Mu Lee
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sue Kyung Park
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sonja I. Berndt
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Douglas Reding
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nilanjan Chatterjee
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Robert Welch
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stephen Chanock
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Wen-Yi Huang
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Richard B. Hayes
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1158/1055-9965.EPI-06-0895 Published June 2007
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading
  • TGFB1
  • prostate cancer
  • PLCO study
  • polymorphism

Introduction

Transforming growth factor β (TGF-β) plays a key role in cell cycle control and carcinogenic processes. TGF-β regulates growth and proliferation of cells and may play a dual role in carcinogenesis, inhibiting early-stage growth and promoting later-stage growth (1). TGF-β1, the predominant TGF-β, stimulates cell differentiation and inhibits epithelial cell proliferation in nonmalignant prostate cells; however, prostate cancer cells exhibit resistance to the growth-inhibitory effect of TGF-β1 (2).

Gene variants in TGFB1 have been related to functional effects. Thus, the gene would seem to be a good prostate cancer susceptibility candidate (2). The TGFB1 10Pro (C) and tightly linked −509T alleles are reported to increase levels of TGF-β1 (3-6). The −800A polymorphism is expected to reduce the affinity for the cAMP-responsive element binding protein family of transcription factors and, thus, to decrease expression of TGF-β1 (4). The Arg-to-Pro polymorphism at codon 25 was associated with lower TGF-β1 production (7, 8). The Thr-to-Ile polymorphism at codon 263 is located in the part of the TGF-β1 pro-protein that is cleaved from the active part of the protein and may thus affect TGF-B1 activation (9).

Japanese males with the TGFB1 TC (Leu/Pro) or TT (Leu/Leu) genotype at codon 10 (+29 position) were reported to have a 1.6-fold increased risk for prostate cancer (10), and American physicians were reported to have a 2.4-fold increased risk for advanced stage prostate cancer in relation to the T allele at TGFB1 position −509, whereas no excess was noted for the codon 10 variant (11).

In the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, we investigated the role of five single-nucleotide polymorphisms (SNP) in TGFB1, chosen because of potential functional significance, in relation to prostate cancer risk. We studied >1,300 prostate cancer cases and a similar number of controls.

Materials and Methods

Study Setting: The PLCO Trial

This nested case-control study was conducted within the screening arm of the PLCO Trial, which was designed to evaluate the effectiveness of prostate, lung, colorectal, and ovarian cancer screening and to investigate etiologic factors and early markers of cancer (12, 13). Participants in the PLCO Trial, ages 55 to 74 years, were recruited at 10 centers in the United States (Birmingham, AL; Denver, CO; Detroit, MI; Honolulu, HI; Marshfield, WI; Minneapolis, MN; Pittsburgh, PA; Salt Lake City, UT; St. Louis, MO; and Washington, DC) between September 1993 and June 2001.

Study Population

Men randomized to the screening arm were eligible for the nested case-control study if they had at least one valid screening for prostate cancer (prostate-specific antigen and/or digital rectal exam) before October 1, 2001 (the censor date for this analysis), completed the baseline risk factor questionnaire, provided a blood sample, and signed the informed consent for etiologic studies of cancer (n = 26,975). All men were followed from their initial valid prostate cancer screen (prostate-specific antigen and/or digital rectal exam) to first occurrence of prostate cancer, loss to follow-up, death, or October 1, 2001, whichever came first. Cases were defined as men diagnosed with adenocarcinoma of the prostate. The eligible group included 1,320 prostate cancer cases (1,213 non-Hispanic Caucasians and 107 African Americans). We selected 1,842 controls (1,433 non-Hispanic Caucasians and 409 African Americans) using risk-set sampling frequency matched by age (5-year intervals), race (whites, 1:1.2; blacks, 1:4), time since initial screening (1-year time windows), and year of blood draw.

Questionnaire Data

At enrollment, all participants were asked to complete a questionnaire including age, ethnicity, education, occupation, current and past smoking behavior, alcohol consumption, history of cancer and other diseases, use of selected drugs, recent history of screening exams, and prostate-related health factors.

Genotyping

Genotype analysis was done at the National Cancer Institute Core Genotyping Facility.7 All TaqMan assays (Applied Biosystems, Inc.) were optimized on the ABI 7900 HT detection system with 100% concordance with sequence analysis of 102 individuals listed on the SNP500Cancer database (14).8

We selected five SNPs with potential functional significance in TGFB1 for analysis: −1639G>A (rs1800468: −800G>A), −1348C>T (rs1800469: −509C>T), Ex1-327C>T (rs1982073: L10P), Ex1-282C>G (rs1800471: P25R), and Ex5-73C>T (rs1800472: T263I).

The genotype distribution of TGFB1 Ex5-73C>T (T263I) deviated from Hardy-Weinberg proportions in Caucasian controls (P = 0.05, exact test); however, the concordance rate for the quality control samples (n = 247), which were replicates from 48 study subjects interspersed throughout each batch, was 100% for TGFB1 Ex5-73C>T (T263I). Therefore, we do not believe that the slight deviation from Hardy-Weinberg proportions for this SNP is due to laboratory error.

Statistical Analysis

To estimate the risk of prostate cancer in relation to SNP genotype, odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using conditional logistic regression in Caucasians and African Americans separately. The analyses were conditioned on the matching factors (i.e., age, time to diagnosis, and year of blood draw). The most prevalent homozygous genotype was used as the reference group. For each SNP, tests for trend were conducted by assigning the ordinal values 1, 2, and 3 for the homozygous wild-type, heterozygous, and homozygous variant genotypes, respectively, and by modeling these scores as a continuous variable.

Haplotype analyses were conducted using the haplo.stats package9 in the R program (v. 2.2.1),10 which uses an expectation-maximization algorithm to estimate haplotypes from genotype data (15). Haplotypes were estimated separately for Caucasians and African Americans excluding subjects with all the genotype data missing. A generalized linear model was used to estimate the effect of individual haplotypes by fitting an additive model for each haplotype, adjusting for the matching factors (age, time to diagnosis, and year of blood draw) in each ethnic group. The overall difference in haplotype frequencies between cases and controls was assessed using a global score test.

Results

Age distribution was similar between cases and controls; mean age was 64.8 ± 5.0 years for cases and 64.5 ± 5.0 years for controls. The proportion of African Americans was higher in controls (22.2%) than in cases (8.1%) as a result of the 4:1 matching scheme for this population. Mean body mass index varied between cases (27.2 kg/m2) and controls (27.6 kg/m2), with marginal significance (P = 0.05). Family history of prostate cancer was a significant risk factor for prostate cancer (P < 0.001). Smoking and alcohol consumption were not different between cases and controls (P = 0.78 and 0.95, respectively).

Minor allele frequencies for five SNPs of TGFB1 in control subjects ranged from 0.01 for Ex5-73T (263T) in African Americans to 0.44 for Ex1-327C (10C) in African Americans. None of the five SNPs studied was significantly associated with prostate cancer risk (Table 1 ). No dominant or recessive effect was found and no test for trend was significant (P > 0.30). Analysis of high-stage (stage ≥III) or high-grade prostate cancer (Gleason score ≥7) also showed similar results (data not shown). Results from haplotype analysis were consistent showing no significant results in Caucasians and African Americans, respectively (Table 2 ).

View this table:
  • View inline
  • View popup
Table 1.

The distributions of genetic polymorphisms of TGFB1 and prostate cancer risk

View this table:
  • View inline
  • View popup
Table 2.

Haplotype distributions of TGFB1 and prostate cancer risk

Discussion

Our large study suggests that selected genetic polymorphisms of potential functional significance in TGFB1 do not play a role in prostate cancer. For Caucasians, our study was sufficiently large to evaluate two previously reported associations (10, 11) with >90% power to detect an OR ≥1.5 (for dominant effect, with minor allele frequency of 0.05 and α = 0.05). In one previous study, in Asians (10), the frequency of Ex1-327C (10C) was 0.54 and the relative risk was 1.6, whereas in the other study, primarily in Caucasians (11), the frequency of −1348T (−509T) was 0.26 and the relative risk was 2.4. Although we presented data for African Americans, sample size was small and conclusions for this group are limited.

The reported association in Caucasians (11) between −1348T (−509T) and prostate cancer was largely limited to cases with extraprostatic or distant metastatic tumors (stage ≥III; n = 157), although no significant association was found for high-grade cases (Gleason score ≥7; n = 133). In our study, we found no association between the selected SNPs and high-stage (stage ≥III) or high-grade prostate cancer (Gleason score ≥7). Our study does not support the reported associations (10, 11) in Caucasians.

Our SNP selection strategy focused on variants of potential functional significance; we did not fully characterize risk in relation to all variation in this gene. HapMap11 reports 21 SNPs in TGFB1, but the majority of variants are not seen in Caucasians and only six polymorphisms have a frequency ≥1% in this population group; of these six SNPs, only the T263I polymorphism was represented in our study; the remaining four SNPs in our study (−800G>A, −509C>T, L10P, and P25R) were not included in HapMap. Our haplotype-based analysis addressed potential cis relationships of the five studied SNPs, finding no further associations of interest. Full haplotype characterization would likely require more extensive genotyping; our results for potentially functional SNPs in TGFB1 suggest that this additional effort may not be warranted.

In summary, we found no evidence of association of prostate cancer with five TGFB1 genetic polymorphisms and their haplotypic combinations in PLCO trial.

Acknowledgments

We thank Drs. Christine Berg and Philip Prorok (Division of Cancer Prevention, National Cancer Institute), the Screening Center investigators and staff for the PLCO Cancer Screening Trial, Tom Riley and staff (Information Management Services, Inc.), Barbara O'Brien and staff (Westat, Inc.), and Drs. Bill Kopp, Wen Shao, and staff (Science Applications International Corporation-Frederick) for their contributions to making this study possible.

Footnotes

  • ↵7 http://cgf.nci.nih.gov

  • ↵8 http://snp500cancer.nci.nih.gov

  • ↵9 http://mayoresearch.mayo.edu/mayo/research/biostat/schaid.cfm

  • ↵10 http://www.r-project.org

  • ↵11 http://www.hapmap.org

  • The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

    • Accepted April 11, 2007.
    • Received October 23, 2006.
    • Revision received February 16, 2007.

References

  1. ↵
    Derynck R, Akhurst RJ, Balmain A. TGF-β signaling in tumor suppression and cancer progression. Nat Genet 2001;29:117–29.
    OpenUrlCrossRefPubMed
  2. ↵
    Barrack ER. TGFβ in prostate cancer: a growth inhibitor that can enhance tumorigenicity. Prostate 1997;31:61–70.
    OpenUrlCrossRefPubMed
  3. ↵
    Dunning AM, Ellis PD, McBride S, et al. A transforming growth factorβ1 signal peptide variant increases secretion in vitro and is associated with increased incidence of invasive breast cancer. Cancer Res 2003;63:2610–5.
    OpenUrlAbstract/FREE Full Text
  4. ↵
    Grainger DJ, Heathcote K, Chiano M, et al. Genetic control of the circulating concentration of transforming growth factor type β1. Hum Mol Genet 1999;8:93–7.
    OpenUrlAbstract/FREE Full Text
  5. Yokoda M, Ichihara S, Lin TL, Nakashima N, Yamada Y. Association of a T29->C polymorphism of the transforming growth factor-β1 gene with genetic susceptibility to myocardial infarction in Japanese. Circulation 2000;101:2783–7.
    OpenUrlAbstract/FREE Full Text
  6. ↵
    Yamada Y, Miyauchi A, Goto J, et al. Association of a polymorphism of the transforming growth factor-β1 gene with genetic susceptibility to osteoporosis in postmenopausal Japanese women. J Bone Miner Res 1998;13:1569–76.
    OpenUrlCrossRefPubMed
  7. ↵
    Awad MR, El-Gamel A, Hasleton P, Turner DM, Sinnott PJ, Hutchinson IV. Genotypic variation in the transforming growth factor-β1 gene: association with transforming growth factor-β1 production, fibrotic lung disease, and graft fibrosis after lung transplantation. Transplantation 1998;66:1014–20.
    OpenUrlCrossRefPubMed
  8. ↵
    Hoffmann SC, Stanley EM, Darrin Cox E, et al. Association of cytokine polymorphic inheritance and in vitro cytokine production in anti-CD3/CD28-stimulated peripheral blood lymphocytes. Transplantation 2001;72:1444–50.
    OpenUrlCrossRefPubMed
  9. ↵
    Cambien F, Ricard S, Troesch A, et al. Polymorphisms of the transforming growth factor-β1 gene in relation to myocardial infarction and blood pressure. The Etude Cas-Temoin de l'Infarctus du Myocarde (ECTIM) Study. Hypertension 1996;28:881–7.
    OpenUrlAbstract/FREE Full Text
  10. ↵
    Li Z, Habuchi T, Tsuchiya N, et al. Increased risk of prostate cancer and benign prostatic hyperplasia associated with transforming growth factor-β1 gene polymorphism at codon10. Carcinogenesis 2004;25:237–40.
    OpenUrlAbstract/FREE Full Text
  11. ↵
    Ewart-Toland A, Chan JM, Yuan J, Balmain A, Ma J. A gain of function TGFB1 polymorphism may be associated with late stage prostate cancer. Cancer Epidemiol Biomarkers Prev 2004;13:759–64.
    OpenUrlAbstract/FREE Full Text
  12. ↵
    Gohagan JK, Prorok PC, Hayes RB, Kramer BS. The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial of the National Cancer Institute: history, organization, and status. Control Clin Trials 2000;21:251–72S.
    OpenUrlCrossRef
  13. ↵
    Hayes RB, Sigurdson A, Moore L, et al. Methods for etiologic and early marker investigations in the PLCO trial. Mutat Res 2005;592:147–54.
    OpenUrlPubMed
  14. ↵
    Packer BR, Yeager M, Burdett L, et al. SNP500Cancer: a public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes. Nucleic Acids Res 2006;34:D617–21.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA. Score tests for association between traits and haplotypes when linkage phase is ambiguous. Am J Hum Genet 2002;70:425–34.
    OpenUrlCrossRefPubMed
PreviousNext
Back to top
Cancer Epidemiology Biomarkers & Prevention: 16 (6)
June 2007
Volume 16, Issue 6
  • Table of Contents
  • Table of Contents (PDF)

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Epidemiology, Biomarkers & Prevention article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Lack of Association of Transforming Growth Factor-β1 Polymorphisms and Haplotypes with Prostate Cancer Risk in the Prostate, Lung, Colorectal, and Ovarian Trial
(Your Name) has forwarded a page to you from Cancer Epidemiology, Biomarkers & Prevention
(Your Name) thought you would be interested in this article in Cancer Epidemiology, Biomarkers & Prevention.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Lack of Association of Transforming Growth Factor-β1 Polymorphisms and Haplotypes with Prostate Cancer Risk in the Prostate, Lung, Colorectal, and Ovarian Trial
Daehee Kang, Kyoung-Mu Lee, Sue Kyung Park, Sonja I. Berndt, Douglas Reding, Nilanjan Chatterjee, Robert Welch, Stephen Chanock, Wen-Yi Huang and Richard B. Hayes
Cancer Epidemiol Biomarkers Prev June 1 2007 (16) (6) 1303-1305; DOI: 10.1158/1055-9965.EPI-06-0895

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Lack of Association of Transforming Growth Factor-β1 Polymorphisms and Haplotypes with Prostate Cancer Risk in the Prostate, Lung, Colorectal, and Ovarian Trial
Daehee Kang, Kyoung-Mu Lee, Sue Kyung Park, Sonja I. Berndt, Douglas Reding, Nilanjan Chatterjee, Robert Welch, Stephen Chanock, Wen-Yi Huang and Richard B. Hayes
Cancer Epidemiol Biomarkers Prev June 1 2007 (16) (6) 1303-1305; DOI: 10.1158/1055-9965.EPI-06-0895
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Diet Quality and Ovarian Cancer Survival
  • PDE5 inhibitors use and precursors of colorectal cancer
  • Association between serum iron biomarkers and breast cancer
Show more Null Results in Brief
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Epidemiology, Biomarkers & Prevention

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Epidemiology, Biomarkers & Prevention
eISSN: 1538-7755
ISSN: 1055-9965

Advertisement